Integrative analysis of the bladder cancer from a cell cycle NCAM1 perspective at both single cell and bulk resolution

Abstract Introduction Bladder cancer (BLCA) is a prevalent and deadly form of urinary cancer, and there is a need for effective therapies, particularly for muscle‐invasive bladder cancer (MIBC). Cell cycle inhibitors show promise in restoring control of the cell cycle in BLCA cells, but their clinical prognosis evaluation is limited. Methods Transcriptome and scRNA‐seq data were collected from the Cancer Genome Atlas Program (TCGA)‐BLCA and GSE190888 cohort, respectively. R software and the Seurat package were used for data analysis, including cell quality control, dimensionality reduction, and identification of differentially expressed genes. Genes related to the cell cycle were obtained from the genecards website, and a protein–protein interaction network analysis was performed using cytoscape software. Functional enrichment analysis, immune infiltration analysis, drug sensitivity analysis, and molecular docking were conducted using various tools and packages. BLCA cell lines were cultured and transfected for in vitro experimental assays, including RT‐qPCR analysis, and CCK‐8 cell viability assays. Results We identified 32 genes as independent risk or protective factors for BLCA prediction. Functional enrichment analysis revealed their involvement in cell cycle regulation, apoptosis, and various signaling pathways. Using these genes, we developed a nomogram for predicting BLCA survival, which displayed high prognosis stratification efficacy in BLCA patients. Four cell cycle associated key genes identified, including NCAM1, HBB, CKD6, and CTLA4. We also identified the main cell types in BLCA patients and investigated the functional differences between epithelial cells based on their expression levels of key genes. Furthermore, we observed a high positive correlative relationship between the infiltration of cancer‐associated fibroblasts and the risk score value. Finally, we conducted in vitro experiments to demonstrate the suppressive role of NCAM1 in BLCA cell proliferation. Conclusion These findings suggest that cell cycle associated genes could serve as potential biomarkers for predicting BLCA prognosis and may represent therapeutic targets for the development of more effective therapies. Hopefully, these findings provide valuable insights into the molecular mechanisms and potential therapeutic targets in BLCA from the perspective of cell cycle. Moreover, NCAM1 was a novel cell proliferation suppressor in the BLCA carcinogenesis.